摘要
由一名新闻记者-机器人和机器学习每日新闻的工作人员新闻编辑-调查人员发布了关于化学工程的新报告。根据来自菲律宾奎松市的新闻，由NewsRx编辑，这项研究表明，“现在对具有数据科学、机器学习(ML)和人工智能（A I）技术技能的工程毕业生的需求正在增长。”这项研究的财政支持者包括菲律宾大学Dil Iman。我们的新闻记者从菲律宾大学的研究中获得了一句话：“世界各地的化学工程(ChemE)系目前正在通过在IR项目中开设人工智能或ML选修课程来解决这一技能差距。然而，由于ML模型的教学和理论探讨的深度尚不清楚,设计这门课程难度很大。本文提出了一门研究生层次的ML课程,旨在使学生能够将ML应用于化学研究。为此,我们设计了一门研究生层次的ML课程,旨在使学生能够将ML应用于化学研究。本课程旨在涵盖广泛的ML模型选择，重点是它们的运动、推导和训练算法，然后是它们在化学相关数据集中的应用。我们认为，这种教授ML的算法方法可以帮助扩大学生的能力，因为他们可以自己判断何时使用哪种工具，即使是处理工业以外的问题。我们发现，只要每一个题目都能得到适当的激发，并且填补所要求的统计和计算机科学概念的空白，学生就能继续专注于数学细节。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators publish new report on chemical engi neering. According to news originating from Quezon City, Philippines, by NewsRx editors, the research stated, "The demand for engineering graduates with technic al skills in data science, machine learning (ML), and artificial intelligence (A I) is now growing." Financial supporters for this research include University of The Philippines Dil iman. Our news journalists obtained a quote from the research from University of the P hilippines: "Chemical engineering (ChemE) departments around the world are curre ntly addressing this skills gap by instituting AI or ML elective courses in thei r program. However, designing such a course is difficult since the issue of whic h ML models to teach and the depth of theory to be discussed remains unclear. In this paper, we present a graduate-level ML course particularly designed such th at students will be able to apply ML for research in ChemE. To achieve this, the course intends to cover a wide selection of ML models with emphasis on their mo tivations, derivations, and training algorithms, followed by their applications to ChemE-related data sets. We argue that this algorithmic approach to teaching ML can help broaden the capabilities of students since they can judge for themse lves which tool to use when, even for problems outside the process industries, o r they can modify the methods to test novel ideas. We found that students remain engaged in the mathematical details as long as every topic is properly motivate d and the gaps in the required statistical and computer science concepts are fil led."
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